Industries
Kerry Back

Definition of Industries
- Industry groupings are usually built on SIC codes
- We’ll use a couple of examples: Fama-French 12 industries and Fama-French 48 industries
- The mapping SIC code \(\mapsto\) industry can be found on French’s website
- Here are the 12 industries:
|
start |
end |
| industry |
|
|
| Consumer Nondurables |
100 |
999 |
| Consumer Nondurables |
2000 |
2399 |
| Consumer Nondurables |
2700 |
2749 |
| Consumer Nondurables |
2770 |
2799 |
| Consumer Nondurables |
3100 |
3199 |
| Consumer Nondurables |
3940 |
3989 |
| Consumer Durables |
2500 |
2519 |
| Consumer Durables |
2590 |
2599 |
| Consumer Durables |
3630 |
3659 |
| Consumer Durables |
3710 |
3711 |
| Consumer Durables |
3714 |
3714 |
| Consumer Durables |
3716 |
3716 |
| Consumer Durables |
3750 |
3751 |
| Consumer Durables |
3792 |
3792 |
| Consumer Durables |
3900 |
3939 |
| Consumer Durables |
3990 |
3999 |
| Manufacturing |
2520 |
2589 |
| Manufacturing |
2600 |
2699 |
| Manufacturing |
2750 |
2769 |
| Manufacturing |
3000 |
3099 |
| Manufacturing |
3200 |
3569 |
| Manufacturing |
3580 |
3629 |
| Manufacturing |
3700 |
3709 |
| Manufacturing |
3712 |
3713 |
| Manufacturing |
3715 |
3715 |
| Manufacturing |
3717 |
3749 |
| Manufacturing |
3752 |
3791 |
| Manufacturing |
3793 |
3799 |
| Manufacturing |
3830 |
3839 |
| Manufacturing |
3860 |
3899 |
| Energy |
1200 |
1399 |
| Energy |
2900 |
2999 |
| Chemicals |
2800 |
2829 |
| Chemicals |
2840 |
2899 |
| Business Equipment |
3570 |
3579 |
| Business Equipment |
3660 |
3692 |
| Business Equipment |
3694 |
3699 |
| Business Equipment |
3810 |
3829 |
| Business Equipment |
7370 |
7379 |
| Telecommunications |
4800 |
4899 |
| Utilities |
4900 |
4949 |
| Shops |
5000 |
5999 |
| Shops |
7200 |
7299 |
| Shops |
7600 |
7699 |
| Healthcare |
2830 |
2839 |
| Healthcare |
3693 |
3693 |
| Healthcare |
3840 |
3859 |
| Healthcare |
8000 |
8099 |
| Finance |
6000 |
6999 |
Dummy variables
- We can use categorical variables in numerical models by creating dummy variables.
- We create a dummy variable for each industry defined as: =1 if the firm is in the industry and =0 otherwise.
- If we include dummy variables in a linear regression, we allow each industry to have a different intercept.